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Quasi-Concave and Nonconcave FMODM Problems

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Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 16))

Abstract

A membership function may be concave-shaped or convex-shaped. In this chapter, first, concave and convex membership values are analyzed and, in practice, commonly used approaches for solving an fuzzy multi-objective decision-making (FMODM) problem are briefly reviewed. Then, some proposition and remarks are presented to solve a quasi-concave FMODM problem. The proposed method can directly solve a quasi-concave FMODM problem by using standard LP techniques.

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References

  • Abdelaziz, F.B., Enneifar, L., and Martel, J.M., 2004, A multiobjective fuzzy stochastic program for water resources optimization: The case of lake management, INFOR, 42: 201-215.

    Google Scholar 

  • Biswal, M.P., 1997, Use of projective and scaling algorithm to solve multi-objective fuzzy linear programming problems, The Journal of Fuzzy Mathematics, 5: 439-448.

    MATH  MathSciNet  Google Scholar 

  • Hannan, E.L., 1981a, Linear programming with multiple fuzzy goals, Fuzzy Sets and Systems, 6: 235-248.

    Article  MATH  MathSciNet  Google Scholar 

  • Hannan, E.L., 1981b, On fuzzy goal programming, Decision Sciences, 12: 522-531.

    Article  Google Scholar 

  • Inuiguchi, M., Ichihashi, H., and Kume, Y., 1990, A solution algorithm for fuzzy linear programming with piecewise linear membership functions, Fuzzy Sets and Systems, 34: 15-31.

    Article  MATH  MathSciNet  Google Scholar 

  • Lai, Y.J., and Hwang, C.L., 1994, Fuzzy Multiple Objective Decision Making, Springer-Verlag, New York.

    MATH  Google Scholar 

  • Li, H.L., 1996, Technical note: An efficient method for solving linear goal programming problems, Journal of Optimization Theory and Applications, 90: 465-469.

    Article  MATH  MathSciNet  Google Scholar 

  • Li, H.L., and Yu, C.S., 1999, Comments on “fuzzy programming with nonlinear membership functions …,” Fuzzy Sets and Systems, 101: 109-113.

    Article  MATH  MathSciNet  Google Scholar 

  • Mjelde, K.M., 1983, Fractional resource allocation with S-shaped return functions, Journal of Operational Research Society, 34(7): 627-632.

    Article  MATH  MathSciNet  Google Scholar 

  • Nakamura, K., 1984, Some extensions of fuzzy linear programming, Fuzzy Sets and Systems, 14: 211-229.

    Article  MATH  MathSciNet  Google Scholar 

  • Narasimhan, R., 1980, Goal programming in a fuzzy environment, Decision Sciences, 11: 325-336.

    Article  MathSciNet  Google Scholar 

  • Romero, C., 1994, Handbook of Critical Issues in Goal Programming, Pergamon Press, New York.

    Google Scholar 

  • LINGO 9.0, 2005, LINDO System Inc., Chicago.

    Google Scholar 

  • Simon, H.A., 1960, Some further notes on a class of skew distribution functions, Information and Control, 3: 80-88.

    Article  MATH  Google Scholar 

  • Yang, T., Ignizio, J.P., and Kim, H.J., 1991, Fuzzy programming with nonlinear membership functions: piecewise linear approximation, Fuzzy Sets and Systems, 41: 39-53.

    Article  MATH  MathSciNet  Google Scholar 

  • Yu, C.S., and Li, H.L., 2000, Method for solving quasi-concave and non-concave fuzzy multi-objective programming problems, Fuzzy Sets and Systems, 109: 59-82.

    Article  MATH  MathSciNet  Google Scholar 

  • Yu, C.S., 2001, A Method For Solving Quasi-Concave Or General Non-Concave Fuzzy Multi-Objective Programming Problems And Its Applications In Logistic Management, Marketing Strategies, And Investment Decision-Making, National Science Council of R.O.C., Taipei.

    Google Scholar 

  • Zimmermann, H.J., 1976, Description and optimization of fuzzy systems, International Journal of General Systems, 2: 209-215.

    Article  Google Scholar 

  • Zimmermann, H.J., 1981, Fuzzy programming and linear programming with several objective functions, Fuzzy Sets and Systems, 1: 45-55.

    Article  Google Scholar 

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Yu, CS., Li, HL. (2008). Quasi-Concave and Nonconcave FMODM Problems. In: Kahraman, C. (eds) Fuzzy Multi-Criteria Decision Making. Springer Optimization and Its Applications, vol 16. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-76813-7_14

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